Green synthesis of 1,3-dihydrobenzimidazol-2-ones from aromatic diamines by microwave in a tetrabutylammonium bromide–ethanol molten salt paste

Environmental Chemistry Letters - The replacement of hazardous solvents by greener alternatives is a major goal in green chemistry. Benzimidazol-2-ones are heterocycles exhibiting a wide range of...     

An improved optimization model for predicting Pb recovery efficiency from residual of liberator cells: a hybrid of support vector regression and modified tunicate swarm algorithm

Journal of Material Cycles and Waste Management - In this study, a hybrid of support vector regression and a modified tunicate swarm algorithm (SVR-MTSA) strategy is developed to optimize the...     

The detection of drowsiness using a driver monitoring system

Abstract

Objective: Drowsiness is a major cause of driver impairment leading to crashes and fatalities. Research has established the ability to detect drowsiness with various kinds of sensors. We studied drowsy driving in a high-fidelity driving simulator and evaluated the ability of an automotive production-ready driver monitoring system (DMS) to detect drowsy driving. Additionally, this feature was compared to and combined with signals from vehicle-based sensors.

Methods: The National Advanced Driving Simulator was used to expose drivers to long, monotonous drives. Twenty participants drove for about 4?h in the simulator between 10 p.m. and 2 a.m. They were allowed to use cruise control and traffic was sparse and semirandom, with both slower- and faster-moving vehicles. Observational ratings of drowsiness (ORDs) were used as the ground truth for drowsiness, and several dependent measures were calculated from vehicle and DMS signals. Drowsiness classification models were created that used only vehicle signals, only driver monitoring signals, and a combination of the 2 sources.

Results: The model that used DMS signals performed better than the one that used only vehicle signals; however, the combination of the two performed the best. The models were effective at discriminating low levels of drowsiness from moderate to severe drowsiness; however, they were not effective at telling the difference between moderate and severe levels. A binary model that lumped drowsiness into 2 classes had an area under the receiver operating characteristic (ROC) curve of 0.897.

Conclusions: Blinks and saccades have been shown to be predictive of microsleeps; however, it may be that detection of microsleeps and lane departures occurs too late. Therefore, it is encouraging that the model was able to distinguish mild from moderate drowsy driving. The use of automation may make vehicle-based signals useless for characterizing driver states, providing further motivation for a DMS. Future improvements in impairment detection systems may be expected through a combination of improved hardware, physiological measures from unobtrusive sensors and wearables, and the intelligent integration of environmental variables like time of day and time on task.     

Impact of roof rain water harvesting of runoff capture and household consumption

Environmental Science and Pollution Research - In recent years, the occurrence of floods is one of the most important challenges facing in Hamadan city. In the absence/inefficiency of urban...     

Evaluation of physico-chemical properties of biochar-based mixtures for soilless growth media

Journal of Material Cycles and Waste Management - This study was done to evaluate the suitability of biochar-based mixtures for growth media. Biochars from agricultural wastes were produced by slow...     

Composting plant leachate treatment by a pilot-scale,three-stage,horizontal flow constructed wetland in central Iran

Environmental Science and Pollution Research - Handling and treatment of composting leachate is difficult and poses major burdens on composting facilities. The main goal of this study was to...     

Viability of combining microalgae and macroalgae cultures for treating anaerobically digested piggery effluent

Algal phytoremediation represents a practical green solution for treating anaerobically digested piggery effluent(ADPE). The potential and viability of combining microalgae and macroalgae cultivation for the efficient treatment of ADPE were evaluated in this study.Bioprospecting the ability of different locally isolated macroalgae species illustrated the potential of Cladophora sp. to successfully grow and treat ADPE with up to 150 mg/L NH_4~+ with a biomass productivity of(0.13 ± 0.02) g/(L·day) and ammonium removal rate of(10.23 ± 0.18) mg/(L·day) NH_4~+. When grown by itself, the microalgae consortium used in this study consisting of Chlorella sp. and Scenedesmus sp. was found to grow and treat undiluted ADPE(up to 525 mg/L NH_4~+) with an average ammonium removal rate of 25 mg/(L·day) NH_4~+ and biomass productivity of(0.012 ± 0.0001) g/(L·day). Nevertheless, when combined together, despite the different cultivation systems(attached and non-attached) evaluated,microalgae and macroalgae were unable to co-exist together and treat ADPE as their respective growth were inversely related to each other due to direct competition for nutrients and available resources as well as the negative physical interaction between both algal groups.     

Anaerobic codigestion of municipal, farm, and industrial organic wastes: a survey of recent literature.

Codigestion of organic wastes is a technology that is increasingly being applied for simultaneous treatment of several solid and liquid organic wastes. The main advantages of this technology are improved methane yield because of the supply of additional nutrients from the codigestates and more efficient use of equipment and cost-sharing by processing multiple waste streams in a single facility. Many municipal wastewater treatment plants (WWTPs) in industrialized countries currently process wastewater sludge in large digesters. Codigestion of organic wastes with municipal wastewater sludge can increase digester gas production and provide savings in the overall energy costs of plant operations. Methane recovery also helps to reduce the emission of greenhouse gases to the atmosphere. The goal of this literature survey was to summarize the research conducted in the last four years on anaerobic codigestion to identify applications of codigestion at WWTPs. Because the solids content in municipal wastewater sludge is low, this survey only focuses on codigestion processes operated at relative low solids content (slurry mode). Semi-solid or solid codigestion processes were not included. Municipal wastewater sludge, the organic fraction of municipal solid waste, and cattle manure (CAM) are the main wastes most often used in codigestion processes. Wastes that are codigested with these main wastes are wood wastes, industrial organic wastes, and farm wastes. These are referred to in this survey as codigestates. The literature provides many laboratory studies (batch assays and bench-scale digesters) that assess the digestibility of codigestates and evaluate the performance and monitoring of codigestion, inhibition of digestion by codigestates, the design of the process (e.g., single-stage or two-stage processes), and the operation temperature (e.g., mesophilic or thermophilic). Only a few reports on pilot- and full-scale studies were found. These evaluate general process performance and pretreatment of codigestates, energy production, and treatment costs.